Hypertrophic cardiomyopathy is a benign disease in an unselected population with a low incidence of cardiac death. Syncope was associated with a higher incidence of SCD and patients with a significant LVOT obstruction were more susceptible to clinical deterioration.

Currently, there is little agreement as to how Natural Language Generation (NLG) systems should be evaluated, with a particularly high degree of variation in the way that human evaluation is carried out. This paper provides an overview of how human evaluation is currently conducted, and presents a set of best practices, grounded in the literature. With this paper, we hope to contribute to the quality and consistency of human evaluations in NLG.

Traditionally, most data-to-text applications have been designed using a modular pipeline architecture, in which non-linguistic input data is converted into natural language through several intermediate transformations. By contrast, recent neural models for data-to-text generation have been proposed as end-to-end approaches, where the non-linguistic input is rendered in natural language with much less explicit intermediate representations in between. This study introduces a systematic comparison between neural pipeline and endto-end data-to-text approaches for the generation of text from RDF triples. Both architectures were implemented making use of the encoder-decoder Gated-Recurrent Units (GRU) and Transformer, two state-of-the art deep learning methods. Automatic and human evaluations together with a qualitative analysis suggest that having explicit intermediate steps in the generation process results in better texts than the ones generated by end-to-end approaches. Moreover, the pipeline models generalize better to unseen inputs. Data and code are publicly available. 1

Background-Mitral leaflet extension (MLE) combined with septal myectomy is a new surgical approach to treat hypertrophic obstructive cardiomyopathy (HOCM) and an enlarged mitral leaflet area. The study presents the long-term clinical results and outcome of this technique. Methods and Results-MLE entails grafting a glutaraldehyde-preserved autologous pericardial patch onto the center portion of the anterior mitral valve leaflet. Twenty-nine patients with HOCM were studied. Mean follow-up (ϮSD) was 3.4Ϯ2.1 years (range 3 months to 7.7 years). The preoperative calculated mitral leaflet area was 16.7Ϯ3.4 cm 2 . New York Heart Association functional class improved significantly from 2.8Ϯ0.4 to 1.3Ϯ0.4 (PϽ0.05), width of the interventricular septum decreased from 23Ϯ4 to 17Ϯ2 mm (PϽ0.05), left ventricular outflow tract gradient decreased from 100Ϯ20 to 17Ϯ14 mm Hg (PϽ0.01), severity of mitral regurgitation graded on a scale from 0 to 4ϩ decreased from 2.5Ϯ0.9 to 0.5Ϯ0.6 (PϽ0.01), and severity of the systolic anterior motion of the mitral valve graded on a scale from 0 to 3ϩ decreased from 2.9Ϯ0.3 to 0.5Ϯ0.7 (PϽ0.01) postoperatively. There were no deaths associated with surgery. Conclusions-Long-term follow-up shows sustained improvement in functional status, reduction of outflow tract obstruction, and attenuation of mitral regurgitation and systolic anterior motion of the mitral valve. In this respect, the new technique widens the surgical applications in HOCM.

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